{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 决战AI安全 - 机器学习基本实验\n",
    "\n",
    "## 1. 线性回归数据预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn import datasets, linear_model\n",
    "from sklearn.metrics import mean_squared_error, r2_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "diabetes_X, diabetes_y = datasets.load_diabetes(return_X_y=True)\n",
    "diabetes_X = diabetes_X[:, np.newaxis, 2]\n",
    "diabetes_X_train = diabetes_X[:-20]\n",
    "diabetes_X_test = diabetes_X[-20:]\n",
    "diabetes_y_train = diabetes_y[:-20]\n",
    "diabetes_y_test = diabetes_y[-20:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 建立模型并训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(diabetes_X_train, diabetes_y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 测试预测效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: \n",
      " [938.23786125]\n",
      "Mean squared error: 2548.07\n",
      "Coefficient of determination: 0.47\n"
     ]
    }
   ],
   "source": [
    "# Make predictions using the testing set\n",
    "diabetes_y_pred = regr.predict(diabetes_X_test)\n",
    "\n",
    "# The coefficients\n",
    "print('Coefficients: \\n', regr.coef_)\n",
    "# The mean squared error\n",
    "print('Mean squared error: %.2f'\n",
    "      % mean_squared_error(diabetes_y_test, diabetes_y_pred))\n",
    "# The coefficient of determination: 1 is perfect prediction\n",
    "print('Coefficient of determination: %.2f'\n",
    "      % r2_score(diabetes_y_test, diabetes_y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([236.08568105])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regr.predict(diabetes_X_test[6:7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "310.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes_y_test[6]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 画图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot outputs\n",
    "plt.scatter(diabetes_X_test, diabetes_y_test,  color='black')\n",
    "plt.plot(diabetes_X_test, diabetes_y_pred, color='blue', linewidth=3)\n",
    "\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 逻辑回归数据预测\n",
    "\n",
    "### 2.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "np.set_printoptions(suppress=True)\n",
    "X, y = load_iris(return_X_y=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 建立模型并训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "                   intercept_scaling=1, l1_ratio=None, max_iter=1000,\n",
       "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
       "                   random_state=0, solver='lbfgs', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = LogisticRegression(random_state=0, max_iter=1000)\n",
    "clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 测试预测效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(X[14:15])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y[14:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.98800254, 0.01199745, 0.        ]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict_proba(X[14:15])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9733333333333334"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 逻辑回归数据分类\n",
    "\n",
    "### 3.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import datasets\n",
    "\n",
    "iris = datasets.load_iris()\n",
    "X = iris.data[:, :2]\n",
    "Y = iris.target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 建立模型并训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9866666666666667"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logreg = LogisticRegression(C=1e5)\n",
    "logreg.fit(X, Y)\n",
    "logreg.score(X,Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 可视化效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def changeY(Y):\n",
    "    for index in range(Y.shape[0]):\n",
    "        if Y[index] == 1:\n",
    "            Y[index] = 12\n",
    "    return Y\n",
    "\n",
    "x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\n",
    "y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\n",
    "h = .02\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
    "Z = logreg.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "Z = Z.reshape(xx.shape)\n",
    "Y_ = changeY(Y)\n",
    "plt.figure(1, figsize=(4, 3))\n",
    "plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=Y, edgecolors='k', cmap=plt.cm.Paired)\n",
    "plt.xlabel('Sepal length')\n",
    "plt.ylabel('Sepal width')\n",
    "plt.xlim(xx.min(), xx.max())\n",
    "plt.ylim(yy.min(), yy.max())\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 朴素贝叶斯分类\n",
    "\n",
    "### 4.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "X, y = load_iris(return_X_y=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.2 建立模型并训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianNB(priors=None, var_smoothing=1e-09)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = GaussianNB()\n",
    "clf.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(X[14:15,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y[14:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.96"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(X,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. SVM 数据分类\n",
    "\n",
    "### 5.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn import datasets, svm, metrics\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "digits = datasets.load_digits()\n",
    "_, axes = plt.subplots(2, 4)\n",
    "images_and_labels = list(zip(digits.images, digits.target))\n",
    "for ax, (image, label) in zip(axes[0, :], images_and_labels[:4]):\n",
    "    ax.set_axis_off()\n",
    "    ax.imshow(image, cmap=plt.cm.gray_r, interpolation='nearest')\n",
    "    ax.set_title('Training: %i' % label)\n",
    "\n",
    "n_samples = len(digits.images)\n",
    "data = digits.images.reshape((n_samples, -1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 建立模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=1.0, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n",
       "    decision_function_shape='ovr', degree=3, gamma=0.001, kernel='rbf',\n",
       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "    tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier = svm.SVC(gamma=0.001)\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    data, digits.target, test_size=0.5, shuffle=False)\n",
    "classifier.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9688542825361512\n"
     ]
    }
   ],
   "source": [
    "predicted = classifier.predict(X_test)\n",
    "print(classifier.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification report for classifier SVC(C=1.0, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n",
      "    decision_function_shape='ovr', degree=3, gamma=0.001, kernel='rbf',\n",
      "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
      "    tol=0.001, verbose=False):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.99      0.99        88\n",
      "           1       0.99      0.97      0.98        91\n",
      "           2       0.99      0.99      0.99        86\n",
      "           3       0.98      0.87      0.92        91\n",
      "           4       0.99      0.96      0.97        92\n",
      "           5       0.95      0.97      0.96        91\n",
      "           6       0.99      0.99      0.99        91\n",
      "           7       0.96      0.99      0.97        89\n",
      "           8       0.94      1.00      0.97        88\n",
      "           9       0.93      0.98      0.95        92\n",
      "\n",
      "    accuracy                           0.97       899\n",
      "   macro avg       0.97      0.97      0.97       899\n",
      "weighted avg       0.97      0.97      0.97       899\n",
      "\n",
      "\n",
      "Confusion matrix:\n",
      "[[87  0  0  0  1  0  0  0  0  0]\n",
      " [ 0 88  1  0  0  0  0  0  1  1]\n",
      " [ 0  0 85  1  0  0  0  0  0  0]\n",
      " [ 0  0  0 79  0  3  0  4  5  0]\n",
      " [ 0  0  0  0 88  0  0  0  0  4]\n",
      " [ 0  0  0  0  0 88  1  0  0  2]\n",
      " [ 0  1  0  0  0  0 90  0  0  0]\n",
      " [ 0  0  0  0  0  1  0 88  0  0]\n",
      " [ 0  0  0  0  0  0  0  0 88  0]\n",
      " [ 0  0  0  1  0  1  0  0  0 90]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "images_and_predictions = list(zip(digits.images[n_samples // 2:], predicted))\n",
    "for ax, (image, prediction) in zip(axes[1, :], images_and_predictions[:4]):\n",
    "    ax.set_axis_off()\n",
    "    ax.imshow(image, cmap=plt.cm.gray_r, interpolation='nearest')\n",
    "    ax.set_title('Prediction: %i' % prediction)\n",
    "\n",
    "print(\"Classification report for classifier %s:\\n%s\\n\"\n",
    "      % (classifier, metrics.classification_report(y_test, predicted)))\n",
    "disp = metrics.plot_confusion_matrix(classifier, X_test, y_test)\n",
    "disp.figure_.suptitle(\"Confusion Matrix\")\n",
    "print(\"Confusion matrix:\\n%s\" % disp.confusion_matrix)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. k-means数据聚类\n",
    "\n",
    "### 6.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn import datasets\n",
    "\n",
    "np.random.seed(5)\n",
    "\n",
    "iris = datasets.load_iris()\n",
    "X = iris.data\n",
    "y = iris.target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 完成聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "estimators = [('k_means_iris_8', KMeans(n_clusters=8)),\n",
    "              ('k_means_iris_3', KMeans(n_clusters=3)),\n",
    "              ('k_means_iris_bad_init', KMeans(n_clusters=3, n_init=1,\n",
    "                                               init='random'))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.3 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\dev_tools\\anaconda\\lib\\site-packages\\ipykernel_launcher.py:47: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fignum = 1\n",
    "titles = ['8 clusters', '3 clusters', '3 clusters, bad initialization']\n",
    "for name, est in estimators:\n",
    "    fig = plt.figure(fignum, figsize=(4, 3))\n",
    "    ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
    "    est.fit(X)\n",
    "    labels = est.labels_\n",
    "\n",
    "    ax.scatter(X[:, 3], X[:, 0], X[:, 2],\n",
    "               c=labels.astype(np.float), edgecolor='k')\n",
    "\n",
    "    ax.w_xaxis.set_ticklabels([])\n",
    "    ax.w_yaxis.set_ticklabels([])\n",
    "    ax.w_zaxis.set_ticklabels([])\n",
    "    ax.set_xlabel('Petal width')\n",
    "    ax.set_ylabel('Sepal length')\n",
    "    ax.set_zlabel('Petal length')\n",
    "    ax.set_title(titles[fignum - 1])\n",
    "    ax.dist = 12\n",
    "    fignum = fignum + 1\n",
    "\n",
    "# Plot the ground truth\n",
    "fig = plt.figure(fignum, figsize=(4, 3))\n",
    "ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
    "\n",
    "for name, label in [('Setosa', 0),\n",
    "                    ('Versicolour', 1),\n",
    "                    ('Virginica', 2)]:\n",
    "    ax.text3D(X[y == label, 3].mean(),\n",
    "              X[y == label, 0].mean(),\n",
    "              X[y == label, 2].mean() + 2, name,\n",
    "              horizontalalignment='center',\n",
    "              bbox=dict(alpha=.2, edgecolor='w', facecolor='w'))\n",
    "# Reorder the labels to have colors matching the cluster results\n",
    "y = np.choose(y, [1, 2, 0]).astype(np.float)\n",
    "ax.scatter(X[:, 3], X[:, 0], X[:, 2], c=y, edgecolor='k')\n",
    "\n",
    "ax.w_xaxis.set_ticklabels([])\n",
    "ax.w_yaxis.set_ticklabels([])\n",
    "ax.w_zaxis.set_ticklabels([])\n",
    "ax.set_xlabel('Petal width')\n",
    "ax.set_ylabel('Sepal length')\n",
    "ax.set_zlabel('Petal length')\n",
    "ax.set_title('Ground Truth')\n",
    "ax.dist = 12\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. DBSCAN\n",
    "\n",
    "### 7.1 建立数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn import metrics\n",
    "from sklearn.datasets import make_blobs\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "centers = [[1, 1], [-1, -1], [1, -1]]\n",
    "X, labels_true = make_blobs(n_samples=750, centers=centers, cluster_std=0.4, random_state=0)\n",
    "X = StandardScaler().fit_transform(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.2 建立模型并训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "db = DBSCAN(eps=0.3, min_samples=10).fit(X)\n",
    "core_samples_mask = np.zeros_like(db.labels_, dtype=bool)\n",
    "core_samples_mask[db.core_sample_indices_] = True\n",
    "labels = db.labels_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.3 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "unique_labels = set(labels)\n",
    "colors = [plt.cm.Spectral(each)\n",
    "          for each in np.linspace(0, 1, len(unique_labels))]\n",
    "for k, col in zip(unique_labels, colors):\n",
    "    if k == -1:\n",
    "        # Black used for noise.\n",
    "        col = [0, 0, 0, 1]\n",
    "\n",
    "    class_member_mask = (labels == k)\n",
    "\n",
    "    xy = X[class_member_mask & core_samples_mask]\n",
    "    plt.plot(xy[:, 0], xy[:, 1], 'o', markerfacecolor=tuple(col),\n",
    "             markeredgecolor='k', markersize=14)\n",
    "\n",
    "    xy = X[class_member_mask & ~core_samples_mask]\n",
    "    plt.plot(xy[:, 0], xy[:, 1], 'o', markerfacecolor=tuple(col),\n",
    "             markeredgecolor='k', markersize=6)\n",
    "\n",
    "plt.title('Estimated number of clusters: %d' % n_clusters_)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
